Given a 3D revolving structure, a pose-unconstrained multi-line structured-light sensor is used to acquire 3D points of the general section profiles in Fig. 2(a) according to the structured-light vision model[1]}. For each viewpoint, the proposed algorithm for reconstructing the normal section profile works in an iterative mode (Section ).
The axis of the 3D revolving structure is estimated via the corresponding points from multiple general section profiles.
According to the estimated axis, the normal section profile can be estimated by rotating the multiple general profiles onto an axis-crossing plane. In turn, the corresponding points between general section profiles are updated according to the closest point pairs between the estimated normal section profiles. When the correspondence error converges to a minimum, the estimated normal section profiles overlap with each other and are fused to get a final normal section profile. As the profile at one view-point is partial, we register all the partial normal section profiles from multiple single viewpoints using the ICP algorithm[2]}, [3]}, [4]} and obtain a complete normal section profile, as shown in Fig. REF (c). We will detail our models and the iterative optimization algorithm in the following sections.
